We study how noise trading flows impact the cross-section of asset prices in a market where sophisticated investors enforce no-arbitrage. In our model, individual asset flows, aggregated at the factor level, drive fluctuations in factor risk premia, which in turn impact asset prices through beta pricing. This structure fits the reduced-form patterns of how each asset’s flow impacts its own price and other assets’ prices with only a few factor-level parameters. A model-implied trading strategy, designed to exploit the reversion of factor-level price impacts, delivers strong investment outcomes and improves the performance of a wide range of anomaly portfolios.
Notre Dame, Johns Hopkins Carey, RUC-VUW Joint Virtual Research Workshop, 6th Annual Wolfe Global Quantitative and Macro Investment Conference, Federal Reserve Board, Campbell & Company, MFA Annual Meeting 2023, Southern Methodist University, FMCG 2023, SoFiE 2023 Conference, CICF 2023, Chinese University of Hong Kong, City University of Hong Kong, 10th SAFE Asset Pricing Workshop, UT Dallas 2023 Fall Finance Conference
Financial Markets and Corporate Governance Conference Runner-up for Best Paper